CN107576982A - A kind of sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method - Google Patents
A kind of sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method Download PDFInfo
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Abstract
Description
技术领域technical field
本发明属于铀矿地震综合预测方法技术领域，具体涉及一种砂岩型铀矿地震综合预测方法。The invention belongs to the technical field of comprehensive seismic prediction methods for uranium deposits, and in particular relates to a comprehensive seismic prediction method for sandstone-type uranium deposits.
背景技术Background technique
砂岩型铀矿预测评价工作是砂岩型铀矿勘查中一项关键任务。常规地质预测技术主要利用地质调查、钻探资料进行预测，缺点在于预测的成本较高、周期较长；使用地球化学勘查、放射性物探、电磁法等地球物理方法进行预测评价，其结果往往达不到精度要求、效果不佳；而地震勘探技术对于砂岩型铀矿成矿环境有较好的探测精度，使用地震技术对砂岩型铀矿目标储层进行综合预测具有较好的前景。Prediction and evaluation of sandstone-type uranium deposits is a key task in the exploration of sandstone-type uranium deposits. Conventional geological prediction technology mainly uses geological survey and drilling data to make predictions. The disadvantages are that the cost of prediction is high and the cycle is long; geophysical methods such as geochemical exploration, radioactive geophysical prospecting, and electromagnetic methods are used for prediction and evaluation, and the results often fail to reach Accuracy is required and the effect is not good; however, seismic exploration technology has good detection accuracy for sandstone-type uranium ore-forming environment, and the use of seismic technology to comprehensively predict sandstone-type uranium deposits has a good prospect.
发明内容Contents of the invention
本发明要解决的技术问题是提供一种砂岩型铀矿地震综合预测方法，该方法能够快速、有效地预测砂岩型铀矿目标储层的平面展布范围。The technical problem to be solved by the present invention is to provide a comprehensive earthquake prediction method for sandstone-type uranium deposits, which can quickly and effectively predict the planar distribution range of target reservoirs of sandstone-type uranium deposits.
为了实现这一目的，本发明采取的技术方案是：In order to realize this object, the technical scheme that the present invention takes is:
一种砂岩型铀矿地震综合预测方法，该方法包括以下步骤：A comprehensive earthquake prediction method for sandstone-type uranium deposits, the method comprising the following steps:
(1)在研究区，采集一套砂岩型铀矿三维地震纯波数据；(1) In the study area, collect a set of 3D seismic pure wave data of sandstone-type uranium deposits;
采集野外三维地震数据，对野外三维地震数据依次进行处理以得到三维地震纯波数据；Collect field 3D seismic data, and sequentially process the field 3D seismic data to obtain 3D seismic pure wave data;
(2)使用基于模型反演法对步骤(1)的三维地震纯波数据进行反演计算，得到三维波阻抗数据体，进而计算三维岩性数据体；(2) Using the model-based inversion method to invert and calculate the 3D seismic pure wave data in step (1) to obtain a 3D wave impedance data volume, and then calculate a 3D lithology data volume;
(3)求取目标层位砂体的含砂率分布数据，并绘制成等值线图；(3) Obtain the sand content distribution data of the sand body in the target layer, and draw it into a contour map;
利用步骤(2)得到的三维岩性数据体，利用geoview软件的trace math模块计算目标地层的含砂率数据，并绘制平面等值线图；Utilize the three-dimensional lithology data body that step (2) obtains, utilize the trace math module of geoview software to calculate the sand content rate data of target formation, and draw the plane contour map;
(4)求取孔隙度数据与波阻抗数据的关系(4) Calculate the relationship between porosity data and wave impedance data
①在研究区测井曲线中有孔隙度数据、声波数据、密度数据三类测井数据的情况下：使用excel软件或geoview软件的cross plot模块进行孔隙度和波阻抗的交会分析；① When there are three types of logging data in the logging curves of the study area: porosity data, acoustic wave data, and density data: use excel software or the cross plot module of geoview software to perform cross analysis of porosity and wave impedance;
分析时，设置x横轴为波阻抗数据，波阻抗数据＝声波和密度数据的乘积；y纵轴为孔隙度数据；然后通过excel软件或geoview软件的cross plot模块的线性拟合工具拟合出波阻抗转孔隙度的转换式y＝ax+b，y为孔隙度数据，x为波阻抗数据，a，b为需要拟合的参数；During analysis, set the x horizontal axis as wave impedance data, wave impedance data = the product of acoustic wave and density data; the y vertical axis is porosity data; then use the linear fitting tool of the cross plot module of excel software or geoview software to fit The conversion formula of wave impedance to porosity y=ax+b, y is porosity data, x is wave impedance data, a, b are parameters to be fitted;
②在研究区无孔隙度测井数据的情况下：使用下述的公式(1)，将波阻抗转换为孔隙度数据：② In the case of no porosity logging data in the study area: use the following formula (1) to convert wave impedance into porosity data:
其中，AC固体骨架表示岩石固体骨架的声波时差，AC流体表示岩石孔隙间流体的声波时差，IMP为波阻抗数据，POR为孔隙度数据；Among them, AC solid skeleton represents the acoustic time difference of rock solid skeleton, AC fluid represents the acoustic time difference of fluid between rock pores, IMP is wave impedance data, and POR is porosity data;
(5)利用步骤(4)求取的波阻抗转孔隙度的转换关系，将波阻抗数据转换为孔隙度数据，得到目标地层孔隙度数据分布，并绘制等值线图；(5) Utilize the conversion relationship of wave impedance to porosity obtained in step (4), convert the wave impedance data into porosity data, obtain the porosity data distribution of the target formation, and draw a contour map;
(6)利用三维地震纯波数据，提取地震均方根振幅、瞬时相位、弧长3种地震属性，对此三种地震属性进行聚类分析，基于钻孔资料建立约束条件，回归拟合出一种新的地震属性组合；(6) Using the 3D seismic pure wave data, extract three seismic attributes including seismic root mean square amplitude, instantaneous phase, and arc length, perform cluster analysis on these three seismic attributes, establish constraint conditions based on borehole data, and regression fit the A new combination of earthquake attributes;
(7)交会分析上述目标地层含砂率数据、孔隙度分布数据以及地震属性组合分布数据，综合预测砂岩型铀矿成矿有利地段；(7) Cross-analyze the sand content rate data, porosity distribution data and seismic attribute combination distribution data of the above-mentioned target formations, and comprehensively predict favorable locations for sandstone-type uranium deposits;
综合预测砂岩型铀矿成矿有利地段是指对目标地层含砂率分布图中数值大于X的区域、孔隙度值大于Y的区域、地震属性组合值大于Z的区域进行交会分析研究，据此再进行成矿有利地段的综合预测。The comprehensive prediction of sandstone-type uranium ore-forming favorable areas refers to the intersection analysis and research of the areas with a value greater than X in the sand content distribution map of the target formation, the area with a porosity value greater than Y, and the area with a seismic attribute combination value greater than Z. Then make a comprehensive prediction of favorable mineralization areas.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(1)中，通过地震仪采集野外三维地震数据，对野外三维地震数据进行处理的过程是依次进行静校正、去噪、振幅补偿、反褶积、动校叠加、偏移处理。Further, in the above-mentioned comprehensive earthquake prediction method for sandstone-type uranium deposits, in step (1), the field three-dimensional seismic data is collected through a seismograph, and the process of processing the field three-dimensional seismic data is sequentially performing static correction and denoising , Amplitude Compensation, Deconvolution, Motion Correction Overlay, Migration Processing.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(2)中，具体步骤如下：Further, a kind of sandstone-type uranium deposit earthquake comprehensive prediction method as mentioned above, in step (2), specific steps are as follows:
①初始模型的建立：首先收集研究区的钻井数据，对其中的声波曲线和密度曲线进行平滑处理和标准化处理；①Establishment of the initial model: first collect the drilling data in the study area, and smooth and standardize the acoustic curve and density curve;
②利用geoview软件的STRATA模块建立反演初始模型；②Using the STRATA module of the geoview software to establish the initial inversion model;
③波阻抗反演计算：对步骤(1)得到的三维地震纯波数据进行反演计算，得到三维波阻抗数据体；③Wave impedance inversion calculation: perform inversion calculation on the 3D seismic pure wave data obtained in step (1) to obtain a 3D wave impedance data volume;
④确定波阻抗转岩性的门槛值：每个研究区的波阻抗转岩性的门槛值不尽相同，门槛值的确定基于工区岩石物性参数分析；④Determination of the threshold value of wave impedance transformation lithology: the threshold value of wave impedance transformation lithology is different in each research area, and the determination of the threshold value is based on the analysis of rock physical parameters in the work area;
⑤岩性数据计算：基于步骤(2)④得到的波阻抗转岩性的门槛值，将步骤(2)③得到的三维波阻抗数据体转换为三维岩性数据体，三维岩性数据体的形式为LITH(x，y，t)，其中x表示三维地震数据的Inline号，y表示三维地震数据的Xline号，t表示时间；⑤ Calculation of lithology data: Based on the threshold value obtained in step (2) ④ for converting wave impedance to lithology, the 3D wave impedance data volume obtained in step (2) ③ is converted into a 3D lithology data volume. The form is LITH(x, y, t), where x represents the Inline number of the 3D seismic data, y represents the Xline number of the 3D seismic data, and t represents the time;
LITH(x，y，t)数据体的取值为0或1，0表示泥岩，1表示砂岩。The value of LITH(x, y, t) data volume is 0 or 1, 0 means mudstone, 1 means sandstone.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(2)①中，平滑处理时采用3点或5点平滑处理；Further, in the method for comprehensive earthquake prediction of sandstone-type uranium deposits as described above, in step (2)①, 3-point or 5-point smoothing is used for smoothing;
密度数据的3点或5点滑动平均处理分别如以下公式所示：The 3-point or 5-point moving average processing of the density data is shown in the following formula respectively:
●密度3点滑动平均公式：dden(i)＝(dden(i-1)+dden(i)+dden(i+1))/3●Density 3-point moving average formula: d den(i) ＝(d den(i-1) +d den(i) +d den(i+1) )/3
其中，di代表某个采样点的密度值，di-1为该采样点的前一个采样点的密度值，di+1为该采样点的后一个采样点的密度值；Among them, d i represents the density value of a certain sampling point, d i-1 is the density value of the previous sampling point of the sampling point, and d i+1 is the density value of the next sampling point of the sampling point;
●密度5点滑动平均公式：dden(i)＝(dden(i-2)+dden(i-1)+dden(i)+dden(i+1)+dden(i+2))/5●Density 5-point moving average formula: d den(i) ＝(d den(i-2) +d den(i-1) +d den(i) +d den(i+1) +d den(i+ 2) )/5
其中，di代表某采样点的密度值，di-2为该采样点的前两个采样点的密度值，di-1为该采样点的前一个采样点的密度值，di+1为该采样点的后一个采样点的密度值，di+2为该采样点的后两个采样点的密度值；Among them, d i represents the density value of a sampling point, d i-2 is the density value of the first two sampling points of the sampling point, d i-1 is the density value of the previous sampling point of the sampling point, d i+ 1 is the density value of the next sampling point of the sampling point, d i+2 is the density value of the last two sampling points of the sampling point;
声波数据的3点或5点滑动平均处理分别如以下公式所示：The 3-point or 5-point moving average processing of the acoustic wave data is shown in the following formula:
●声波3点滑动平均公式：dson(i)＝(dson(i-1)+dson(i)+dson(i+1))/3●Sonic 3-point moving average formula: dson(i) ＝( dson(i-1) + dson(i) + dson(i+1) )/3
其中，di代表某个采样点的声波值，di-1为该采样点的前一个采样点的声波值，di+1为该采样点的后一个采样点的声波值；Wherein, d i represents the sound wave value of a certain sampling point, d i-1 is the sound wave value of the previous sampling point of the sampling point, and d i+1 is the sound wave value of the next sampling point of the sampling point;
●声波5点滑动平均公式：dson(i)＝(dson(i-2)+dson(i-1)+dson(i)+dson(i+1)+dson(i+2))/5●Sonic 5-point moving average formula: dson(i) ＝( dson(i-2) + dson(i-1) + dson(i) + dson(i+1) + dson(i+ 2) )/5
其中，di代表某采样点的声波值，di-2为该采样点的前两个采样点的声波值，di-1为该采样点的前一个采样点的声波值，di+1为该采样点的后一个采样点的声波值，di+2为该采样点的后两个采样点的声波值；Among them, d i represents the sound wave value of a certain sampling point, d i-2 is the sound wave value of the first two sampling points of the sampling point, d i-1 is the sound wave value of the previous sampling point of the sampling point, d i+ 1 is the sound wave value of the last sampling point of the sampling point, d i+2 is the sound wave value of the last two sampling points of the sampling point;
步骤(2)①中，标准化处理时使用geoview软件的logging nomalize模块进行处理，将用于建立初始模型的井的声波和密度数据标准化至同一值域范围；In step (2) ①, use the logging nomalize module of geoview software to process during standardization, and standardize the acoustic wave and density data of the wells used to establish the initial model to the same range;
步骤(2)②中，建立反演初始模型时：In step (2)②, when establishing the inversion initial model:
在使用geoview软件的STRATA模块进行反演计算时，反演参数的设置是：10-15Hz高截频；叠代次数10～20次；采样率为1ms～2ms；最大阻抗变化范围为25％～50％；预白化率为1％；运算块大小为1ms～2ms，该运算块大小与采样率相同；比例因子为1；When using the STRATA module of geoview software for inversion calculation, the inversion parameter settings are: 10-15Hz high cut-off frequency; the number of iterations is 10-20 times; the sampling rate is 1ms-2ms; the maximum impedance change range is 25%- 50%; the pre-whitening rate is 1%; the operation block size is 1ms ~ 2ms, and the operation block size is the same as the sampling rate; the scaling factor is 1;
反演类型为多道反演，Inline方向10～20道，Xline方向10～20道；The inversion type is multi-channel inversion, with 10-20 channels in the Inline direction and 10-20 channels in the Xline direction;
步骤(2)④中，岩石物性参数分析利用geoview软件的cross plot模块。In step (2)④, the petrophysical parameters were analyzed using the cross plot module of the geoview software.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(3)中，具体步骤如下：Further, a kind of sandstone-type uranium mine earthquake comprehensive prediction method as mentioned above, in step (3), specific steps are as follows:
①基于三维地震纯波数据输入Landmark地震解释软件，将解释得到的三维地层数据导入geoview软件中，将步骤(2)的三维岩性数据体导入geoview软件；① Input the 3D seismic pure wave data into Landmark seismic interpretation software, import the interpreted 3D stratigraphic data into the geoview software, and import the 3D lithology data volume in step (2) into the geoview software;
②确定目标层范围，利用geoview软件的trace math模块在目标层顶底范围内，进行循环统计计算，得到地层含砂率分布数据RATIO(x，y)；② Determine the range of the target layer, use the trace math module of the geoview software to perform circular statistical calculations within the top and bottom range of the target layer, and obtain the sand content distribution data RATIO(x, y) of the formation;
③使用“trace math”模块需要编写代码，具体代码如下：③ To use the "trace math" module, you need to write code, the specific code is as follows:
据此可得到目标地层的含砂率RATIO(x，y)分布数据；According to this, the sand content ratio RATIO (x, y) distribution data of the target formation can be obtained;
④对步骤(3)②中的含砂率RATIO(x，y)数据，进行等值线成图。④ Carry out contour mapping for the sand content ratio RATIO (x, y) data in step (3)②.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(5)中，具体步骤如下：Further, a kind of sandstone-type uranium deposit earthquake comprehensive prediction method as mentioned above, in step (5), specific steps are as follows:
①利用步骤(4)得到的转换关系式，利用geoview软件的trace math模块计算得到孔隙度三维数据体POR(x，y，t)，x表示三维地震数据的Inline号，y表示三维地震数据的Xline号，t表示时间；① Using the conversion relation obtained in step (4), use the trace math module of geoview software to calculate the porosity three-dimensional data volume POR(x, y, t), where x represents the Inline number of the three-dimensional seismic data, and y represents the number of the three-dimensional seismic data Xline number, t means time;
②确定目标层范围，利用geoview软件的trace math模块在目标层顶底范围内，进行循环统计计算，得到目标地层平均孔隙度分布数据POR_AVA(x，y)，x表示三维地震数据的Inline号，y表示三维地震数据的Xline号；② Determine the range of the target layer, use the trace math module of the geoview software to perform circular statistical calculations within the top and bottom range of the target layer, and obtain the average porosity distribution data of the target layer POR_AVA(x, y), where x represents the Inline number of the 3D seismic data, y represents the Xline number of the 3D seismic data;
使用trace math模块编写的代码如下：The code written using the trace math module is as follows:
③据此可得到目标地层的孔隙度POR_AVA(x，y)分布数据；③ Based on this, the porosity POR_AVA(x, y) distribution data of the target formation can be obtained;
④对步骤(5)③中得到的孔隙度POR_AVA(x，y)数据，进行等值线成图。④ Contour mapping is performed on the porosity POR_AVA(x, y) data obtained in step (5)③.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(6)中，将步骤(1)三维地震纯波数据输入至Landmark软件中，确定目标储层的位置，在此位置上下各20ms厚度内提取地震均方根振幅、瞬时相位、弧长3种地震属性，再对此三种地震属性进行聚类分析；Further, in the above-mentioned comprehensive earthquake prediction method for sandstone-type uranium deposits, in step (6), the three-dimensional seismic pure wave data of step (1) is input into the Landmark software to determine the position of the target reservoir, and at this position Extract the three seismic attributes of seismic root mean square amplitude, instantaneous phase and arc length in the upper and lower thicknesses of 20ms, and then perform cluster analysis on these three seismic attributes;
识别不同区域多属性约束情况，在二连盆地砂岩型铀矿区的实际应用中约束情况为：地震均方根振幅属性值大于25、瞬时相位属性值大于0、弧长属性值大于7，据此回归拟合出一种新的地震属性组合的数据，并据此绘制成等值线图。Identify the multi-attribute constraints in different regions. In the actual application of the sandstone-type uranium mining area in the Erlian Basin, the constraints are: the seismic root mean square amplitude attribute value is greater than 25, the instantaneous phase attribute value is greater than 0, and the arc length attribute value is greater than 7. According to this Regression fits the data of a new seismic attribute combination, and draws a contour map accordingly.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(7)中，X、Y、Z值的选取依砂岩型铀矿地区的不同而不同；获取X、Y、Z值的办法是通过将研究区内的所有工业钻孔位置分别投影至目标地层含砂率分布图、孔隙度分布图、地震属性组合图中，读取所有钻孔位置的含砂率值、孔隙度值、地震属性组合值，再将这些含砂率值、孔隙度值、地震属性组合值进行算术平均，得到X、Y、Z值。Further, in the method for comprehensive earthquake prediction of sandstone-type uranium mines as described above, in step (7), the selection of X, Y, and Z values varies according to the area of sandstone-type uranium deposits; obtaining X, Y, and Z values The best way is to project all the industrial drilling positions in the study area to the sand content distribution map, porosity distribution map, and seismic attribute combination map of the target formation respectively, and read the sand content ratio and porosity values of all drilling positions. value, seismic attribute combination value, and then carry out the arithmetic average of these sand content value, porosity value, and seismic attribute combination value to obtain X, Y, and Z values.
进一步的，如上所述的一种砂岩型铀矿地震综合预测方法，步骤(7)中，综合预测步骤为：Further, a kind of sandstone-type uranium mine seismic comprehensive prediction method as mentioned above, in step (7), the comprehensive prediction step is:
①步骤(3)得到的目标地层含砂率分布图中，值域大于0.8的区域标定为有利区A；① In the sand content distribution map of the target formation obtained in step (3), the area with a value range greater than 0.8 is marked as the favorable area A;
②将步骤(5)得到的目标地层平均孔隙度分布图中，值域大于12％的区域标定为有利区B；2. In the average porosity distribution map of the target stratum obtained in step (5), the area where the value range is greater than 12% is marked as favorable area B;
③将步骤(6)得到的地震属性组合的数据等值线图中，值域大于0.45的区域标定为有利区C；3. In the data contour map of the seismic attribute combination obtained in step (6), the region where the value range is greater than 0.45 is demarcated as favorable region C;
④使用制图软件叠合上述A、B、C三片有利区，预测三片有利区的重叠交集区域为I类成矿远景区；预测三片有利区中有两片有利区的重叠交集区域为II类成矿有利区；其他情况不做预测。④ Use mapping software to superimpose the above three favorable areas A, B, and C, and predict that the overlapping and intersecting area of the three favorable areas is a Type I metallogenic prospect area; it is predicted that the overlapping and intersecting area of two of the three favorable areas is Type II favorable mineralization area; other situations are not predicted.
本发明技术方案的有益效果在于：本发明使用地震波阻抗反演法反算地下砂体分布情况，得到与铀成矿有直接关系的目标地层含砂率信息，同时利用钻孔数据统计的转换关系或经验转换关系将目标层波阻抗信息转换为与成矿作用有关的孔隙度信息，最后利用三维地震数据体提取与铀成矿环境相关的敏感地震属性信息，通过这三类信息综合分析研究预测工区的铀成矿潜力，能够达到快速、有效地预测砂岩型铀矿目标储层发育范围的目的。The beneficial effect of the technical solution of the present invention is that: the present invention uses the seismic wave impedance inversion method to back-calculate the distribution of underground sand bodies, obtains the sand content rate information of the target stratum that is directly related to uranium ore-forming, and utilizes the conversion relationship of drilling data statistics at the same time Or the empirical conversion relationship converts the wave impedance information of the target layer into the porosity information related to the mineralization, and finally uses the 3D seismic data volume to extract the sensitive seismic attribute information related to the uranium ore-forming environment, and predicts it through the comprehensive analysis of these three types of information. The uranium ore-forming potential of the work area can achieve the purpose of quickly and effectively predicting the development range of the sandstone-type uranium deposit target reservoir.
具体实施方式detailed description
下面结合具体实施例对本发明技术方案进行详细说明。The technical solutions of the present invention will be described in detail below in conjunction with specific embodiments.
本发明一种砂岩型铀矿地震综合预测方法，该方法包括以下步骤：The present invention is a sandstone-type uranium mine earthquake comprehensive prediction method, the method comprises the following steps:
(1)在研究区，采集一套砂岩型铀矿三维地震纯波数据；(1) In the study area, collect a set of 3D seismic pure wave data of sandstone-type uranium deposits;
通过地震仪采集野外三维地震数据，对野外三维地震数据依次进行处理以得到三维地震纯波数据；The field 3D seismic data is collected by the seismograph, and the field 3D seismic data is sequentially processed to obtain the 3D seismic pure wave data;
对野外三维地震数据进行处理的过程是依次进行静校正、去噪、振幅补偿、反褶积、动校叠加、偏移处理。The process of processing 3D seismic data in the field is sequentially performing static correction, denoising, amplitude compensation, deconvolution, dynamic correction stacking, and migration processing.
(2)使用基于模型反演法对步骤(1)的三维地震纯波数据进行反演计算，得到三维波阻抗数据体，进而计算三维岩性数据体；(2) Using the model-based inversion method to invert and calculate the 3D seismic pure wave data in step (1) to obtain a 3D wave impedance data volume, and then calculate a 3D lithology data volume;
具体步骤如下：Specific steps are as follows:
①初始模型的建立：首先收集研究区的钻井数据，对其中的声波曲线和密度曲线进行平滑处理和标准化处理；①Establishment of the initial model: first collect the drilling data in the study area, and smooth and standardize the acoustic curve and density curve;
步骤(2)①中，平滑处理时采用3点或5点平滑处理；In step (2)①, 3-point or 5-point smoothing is used for smoothing;
密度数据的3点或5点滑动平均处理分别如以下公式所示：The 3-point or 5-point moving average processing of the density data is shown in the following formula respectively:
●密度3点滑动平均公式：dden(i)＝(dden(i-1)+dden(i)+dden(i+1))/3●Density 3-point moving average formula: d den(i) ＝(d den(i-1) +d den(i) +d den(i+1) )/3
其中，di代表某个采样点的密度值，di-1为该采样点的前一个采样点的密度值，di+1为该采样点的后一个采样点的密度值；Among them, d i represents the density value of a certain sampling point, d i-1 is the density value of the previous sampling point of the sampling point, and d i+1 is the density value of the next sampling point of the sampling point;
●密度5点滑动平均公式：dden(i)＝(dden(i-2)+dden(i-1)+dden(i)+dden(i+1)+dden(i+2))/5●Density 5-point moving average formula: d den(i) ＝(d den(i-2) +d den(i-1) +d den(i) +d den(i+1) +d den(i+ 2) )/5
其中，di代表某采样点的密度值，di-2为该采样点的前两个采样点的密度值，di-1为该采样点的前一个采样点的密度值，di+1为该采样点的后一个采样点的密度值，di+2为该采样点的后两个采样点的密度值；Among them, d i represents the density value of a sampling point, d i-2 is the density value of the first two sampling points of the sampling point, d i-1 is the density value of the previous sampling point of the sampling point, d i+ 1 is the density value of the next sampling point of the sampling point, d i+2 is the density value of the last two sampling points of the sampling point;
声波数据的3点或5点滑动平均处理分别如以下公式所示：The 3-point or 5-point moving average processing of the acoustic wave data is shown in the following formula:
●声波3点滑动平均公式：dson(i)＝(dson(i-1)+dson(i)+dson(i+1))/3●Sonic 3-point moving average formula: dson(i) ＝( dson(i-1) + dson(i) + dson(i+1) )/3
其中，di代表某个采样点的声波值，di-1为该采样点的前一个采样点的声波值，di+1为该采样点的后一个采样点的声波值；Wherein, d i represents the sound wave value of a certain sampling point, d i-1 is the sound wave value of the previous sampling point of the sampling point, and d i+1 is the sound wave value of the next sampling point of the sampling point;
●声波5点滑动平均公式：dson(i)＝(dson(i-2)+dson(i-1)+dson(i)+dson(i+1)+dson(i+2))/5●Sonic 5-point moving average formula: dson(i) ＝( dson(i-2) + dson(i-1) + dson(i) + dson(i+1) + dson(i+ 2) )/5
其中，di代表某采样点的声波值，di-2为该采样点的前两个采样点的声波值，di-1为该采样点的前一个采样点的声波值，di+1为该采样点的后一个采样点的声波值，di+2为该采样点的后两个采样点的声波值；Among them, d i represents the sound wave value of a certain sampling point, d i-2 is the sound wave value of the first two sampling points of the sampling point, d i-1 is the sound wave value of the previous sampling point of the sampling point, d i+ 1 is the sound wave value of the last sampling point of the sampling point, d i+2 is the sound wave value of the last two sampling points of the sampling point;
步骤(2)①中，标准化处理时使用geoview软件的logging nomalize模块进行处理，将用于建立初始模型的井的声波和密度数据标准化至同一值域范围；In step (2) ①, use the logging nomalize module of geoview software to process during standardization, and standardize the acoustic wave and density data of the wells used to establish the initial model to the same range;
②利用geoview软件的STRATA模块建立反演初始模型；②Using the STRATA module of the geoview software to establish the initial inversion model;
步骤(2)②中，建立反演初始模型时：In step (2)②, when establishing the inversion initial model:
在使用geoview软件的STRATA模块进行反演计算时，反演参数的设置是：10-15Hz高截频；叠代次数10～20次；采样率为1ms～2ms；最大阻抗变化范围为25％～50％；预白化率为1％；运算块大小为1ms～2ms，该运算块大小与采样率相同；比例因子为1；When using the STRATA module of geoview software for inversion calculation, the inversion parameter settings are: 10-15Hz high cut-off frequency; the number of iterations is 10-20 times; the sampling rate is 1ms-2ms; the maximum impedance change range is 25%- 50%; the pre-whitening rate is 1%; the operation block size is 1ms ~ 2ms, and the operation block size is the same as the sampling rate; the scaling factor is 1;
反演类型为多道反演，Inline方向10～20道，Xline方向10～20道；The inversion type is multi-channel inversion, with 10-20 channels in the Inline direction and 10-20 channels in the Xline direction;
③波阻抗反演计算：对步骤(1)得到的三维地震纯波数据进行反演计算，得到三维波阻抗数据体；③Wave impedance inversion calculation: perform inversion calculation on the 3D seismic pure wave data obtained in step (1) to obtain a 3D wave impedance data volume;
④确定波阻抗转岩性的门槛值：每个研究区的波阻抗转岩性的门槛值不尽相同，门槛值的确定基于工区岩石物性参数分析；④Determination of the threshold value of wave impedance transformation lithology: the threshold value of wave impedance transformation lithology is different in each research area, and the determination of the threshold value is based on the analysis of rock physical parameters in the work area;
步骤(2)④中，岩石物性参数分析利用geoview软件的cross plot模块。In step (2)④, the petrophysical parameters were analyzed using the cross plot module of the geoview software.
⑤岩性数据计算：基于步骤(2)④得到的波阻抗转岩性的门槛值，将步骤(2)③得到的三维波阻抗数据体转换为三维岩性数据体，三维岩性数据体的形式为LITH(x，y，t)，其中x表示三维地震数据的Inline号，y表示三维地震数据的Xline号，t表示时间；⑤ Calculation of lithology data: Based on the threshold value obtained in step (2) ④ for converting wave impedance to lithology, the 3D wave impedance data volume obtained in step (2) ③ is converted into a 3D lithology data volume. The form is LITH(x, y, t), where x represents the Inline number of the 3D seismic data, y represents the Xline number of the 3D seismic data, and t represents the time;
LITH(x，y，t)数据体的取值为0或1，0表示泥岩，1表示砂岩。The value of LITH(x, y, t) data volume is 0 or 1, 0 means mudstone, 1 means sandstone.
(3)求取目标层位砂体的含砂率分布数据，并绘制成等值线图；(3) Obtain the sand content distribution data of the sand body in the target layer, and draw it into a contour map;
利用步骤(2)得到的三维岩性数据体，利用geoview软件的trace math模块计算目标地层的含砂率数据，并绘制平面等值线图；Utilize the three-dimensional lithology data body that step (2) obtains, utilize the trace math module of geoview software to calculate the sand content rate data of target formation, and draw the plane contour map;
具体步骤如下：Specific steps are as follows:
①基于三维地震纯波数据输入Landmark地震解释软件，将解释得到的三维地层数据导入geoview软件中，将步骤(2)的三维岩性数据体导入geoview软件；① Input the 3D seismic pure wave data into Landmark seismic interpretation software, import the interpreted 3D stratigraphic data into the geoview software, and import the 3D lithology data volume in step (2) into the geoview software;
②确定目标层范围，利用geoview软件的trace math模块在目标层顶底范围内，进行循环统计计算，得到地层含砂率分布数据RATIO(x，y)；② Determine the range of the target layer, use the trace math module of the geoview software to perform circular statistical calculations within the top and bottom range of the target layer, and obtain the sand content distribution data RATIO(x, y) of the formation;
③使用“trace math”模块需要编写代码，具体代码如下：③ To use the "trace math" module, you need to write code, the specific code is as follows:
据此可得到目标地层的含砂率RATIO(x，y)分布数据；According to this, the sand content ratio RATIO (x, y) distribution data of the target formation can be obtained;
④对步骤(3)②中的含砂率RATIO(x，y)数据，进行等值线成图。④ Carry out contour mapping for the sand content ratio RATIO (x, y) data in step (3)②.
(4)求取孔隙度数据与波阻抗数据的关系(4) Calculate the relationship between porosity data and wave impedance data
①在研究区测井曲线中有孔隙度数据、声波数据、密度数据三类测井数据的情况下：使用excel软件或geoview软件的cross plot模块进行孔隙度和波阻抗的交会分析；① When there are three types of logging data in the logging curves of the study area: porosity data, acoustic wave data, and density data: use excel software or the cross plot module of geoview software to perform cross analysis of porosity and wave impedance;
分析时，设置x横轴为波阻抗数据，波阻抗数据＝声波和密度数据的乘积；y纵轴为孔隙度数据；然后通过excel软件或geoview软件的cross plot模块的线性拟合工具拟合出波阻抗转孔隙度的转换式y＝ax+b，y为孔隙度数据，x为波阻抗数据，a，b为需要拟合的参数；During analysis, set the x horizontal axis as wave impedance data, wave impedance data = the product of acoustic wave and density data; the y vertical axis is porosity data; then use the linear fitting tool of the cross plot module of excel software or geoview software to fit The conversion formula of wave impedance to porosity y=ax+b, y is porosity data, x is wave impedance data, a, b are parameters to be fitted;
②在研究区无孔隙度测井数据的情况下：使用下述的公式(1)，将波阻抗转换为孔隙度数据：② In the case of no porosity logging data in the study area: use the following formula (1) to convert wave impedance into porosity data:
其中，AC固体骨架表示岩石固体骨架的声波时差，AC流体表示岩石孔隙间流体的声波时差，IMP为波阻抗数据，POR为孔隙度数据；Among them, AC solid skeleton represents the acoustic time difference of rock solid skeleton, AC fluid represents the acoustic time difference of fluid between rock pores, IMP is wave impedance data, and POR is porosity data;
(5)利用步骤(4)求取的波阻抗转孔隙度的转换关系，将波阻抗数据转换为孔隙度数据，得到目标地层孔隙度数据分布，并绘制等值线图；(5) Utilize the conversion relationship of wave impedance to porosity obtained in step (4), convert the wave impedance data into porosity data, obtain the porosity data distribution of the target formation, and draw a contour map;
具体步骤如下：Specific steps are as follows:
①利用步骤(4)得到的转换关系式，利用geoview软件的trace math模块计算得到孔隙度三维数据体POR(x，y，t)，x表示三维地震数据的Inline号，y表示三维地震数据的Xline号，t表示时间；① Using the conversion relation obtained in step (4), use the trace math module of geoview software to calculate the porosity three-dimensional data volume POR(x, y, t), where x represents the Inline number of the three-dimensional seismic data, and y represents the number of the three-dimensional seismic data Xline number, t means time;
②确定目标层范围，利用geoview软件的trace math模块在目标层顶底范围内，进行循环统计计算，得到目标地层平均孔隙度分布数据POR_AVA(x，y)，x表示三维地震数据的Inline号，y表示三维地震数据的Xline号；② Determine the range of the target layer, use the trace math module of the geoview software to perform circular statistical calculations within the top and bottom range of the target layer, and obtain the average porosity distribution data of the target layer POR_AVA(x, y), where x represents the Inline number of the 3D seismic data, y represents the Xline number of the 3D seismic data;
使用trace math模块编写的代码如下：The code written using the trace math module is as follows:
③据此可得到目标地层的孔隙度POR_AVA(x，y)分布数据；③ Based on this, the porosity POR_AVA(x, y) distribution data of the target formation can be obtained;
④对步骤(5)③中得到的孔隙度POR_AVA(x，y)数据，进行等值线成图。④ Contour mapping is performed on the porosity POR_AVA(x, y) data obtained in step (5)③.
(6)利用三维地震纯波数据，提取地震均方根振幅、瞬时相位、弧长3种地震属性，对此三种地震属性进行聚类分析，基于钻孔资料建立约束条件，回归拟合出一种新的地震属性组合；(6) Using the 3D seismic pure wave data, extract three seismic attributes including seismic root mean square amplitude, instantaneous phase, and arc length, perform cluster analysis on these three seismic attributes, establish constraint conditions based on borehole data, and regression fit the A new combination of earthquake attributes;
具体的，将步骤(1)三维地震纯波数据输入至Landmark软件中，确定目标储层的位置，在此位置上下各20ms厚度内提取地震均方根振幅、瞬时相位、弧长3种地震属性，再对此三种地震属性进行聚类分析；Specifically, input the 3D seismic pure wave data in step (1) into the Landmark software to determine the location of the target reservoir, and extract three seismic attributes including seismic root mean square amplitude, instantaneous phase, and arc length within a thickness of 20 ms above and below the location , and then perform cluster analysis on the three seismic attributes;
识别不同区域多属性约束情况，在二连盆地砂岩型铀矿区的实际应用中约束情况为：地震均方根振幅属性值大于25、瞬时相位属性值大于0、弧长属性值大于7，据此回归拟合出一种新的地震属性组合的数据，并据此绘制成等值线图。Identify the multi-attribute constraints in different regions. In the actual application of the sandstone-type uranium mining area in the Erlian Basin, the constraints are: the seismic root mean square amplitude attribute value is greater than 25, the instantaneous phase attribute value is greater than 0, and the arc length attribute value is greater than 7. According to this Regression fits the data of a new seismic attribute combination, and draws a contour map accordingly.
(7)交会分析上述目标地层含砂率数据、孔隙度分布数据以及地震属性组合分布数据，综合预测砂岩型铀矿成矿有利地段；(7) Cross-analyze the sand content rate data, porosity distribution data and seismic attribute combination distribution data of the above-mentioned target formations, and comprehensively predict favorable locations for sandstone-type uranium deposits;
综合预测砂岩型铀矿成矿有利地段是指对目标地层含砂率分布图中数值大于X的区域、孔隙度值大于Y的区域、地震属性组合值大于Z的区域进行交会分析研究，据此再进行成矿有利地段的综合预测。The comprehensive prediction of sandstone-type uranium ore-forming favorable areas refers to the intersection analysis and research of the areas with a value greater than X in the sand content distribution map of the target formation, the area with a porosity value greater than Y, and the area with a seismic attribute combination value greater than Z. Then make a comprehensive prediction of favorable mineralization areas.
X、Y、Z值的选取依砂岩型铀矿地区的不同而不同；获取X、Y、Z值的办法是通过将研究区内的所有工业钻孔位置分别投影至目标地层含砂率分布图、孔隙度分布图、地震属性组合图中，读取所有钻孔位置的含砂率值、孔隙度值、地震属性组合值，再将这些含砂率值、孔隙度值、地震属性组合值进行算术平均，得到X、Y、Z值。The selection of X, Y, and Z values varies according to the sandstone-type uranium deposit area; the way to obtain the X, Y, and Z values is to project the positions of all industrial drilling holes in the research area to the sand content distribution map of the target formation , porosity distribution map, and seismic attribute combination map, read the sand content rate, porosity value, and seismic attribute combination value of all drilling positions, and then perform these sand content rate values, porosity values, and seismic attribute combination values Arithmetic mean to get X, Y, Z values.
综合预测步骤为：The comprehensive forecasting steps are:
①步骤(3)得到的目标地层含砂率分布图中，值域大于0.8的区域标定为有利区A；① In the sand content distribution map of the target formation obtained in step (3), the area with a value range greater than 0.8 is marked as the favorable area A;
②将步骤(5)得到的目标地层平均孔隙度分布图中，值域大于12％的区域标定为有利区B；2. In the average porosity distribution map of the target stratum obtained in step (5), the area where the value range is greater than 12% is marked as favorable area B;
③将步骤(6)得到的地震属性组合的数据等值线图中，值域大于0.45的区域标定为有利区C；3. In the data contour map of the seismic attribute combination obtained in step (6), the region where the value range is greater than 0.45 is demarcated as favorable region C;
④使用制图软件叠合上述A、B、C三片有利区，预测三片有利区的重叠交集区域为I类成矿远景区；预测三片有利区中有两片有利区的重叠交集区域为II类成矿有利区；其他情况不做预测。④ Use mapping software to superimpose the above three favorable areas A, B, and C, and predict that the overlapping and intersecting area of the three favorable areas is a Type I metallogenic prospect area; it is predicted that the overlapping and intersecting area of two of the three favorable areas is Type II favorable mineralization area; other situations are not predicted.
Claims (10)
- A kind of 1. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method, it is characterised in that：This method comprises the following steps：(1) in research area, a set of sandstone-type uranium mineralization with respect 3-D seismics pure wave data are gathered；Field 3D seismic data is gathered, field 3D seismic data is handled successively to obtain 3-D seismics pure wave number According to；(2) Inversion Calculation is carried out to the 3-D seismics pure wave data of step (1) using based on modeling inversion, obtains three-dimensional wave resistance Anti- data volume, and then calculate three-dimensional lithology data body；(3) the sand factor distributed data of destination layer position sand body is asked for, and is depicted as isogram；The three-dimensional lithology data body obtained using step (2), using the trace math modules of geoview softwares with calculating target The sand factor data of layer, and draw plane equivalence；(4) relation of porosity data and Acoustic Impedance Data is asked for1. in the case where having porosity data, sonic data, the class log data of density data three in studying area's log：Make The intersection that porosity and wave impedance are carried out with the cross plot modules of excel softwares or geoview softwares is analyzed；During analysis, the product that x transverse axis is Acoustic Impedance Data, Acoustic Impedance Data=sound wave and density data is set；The y longitudinal axis is hole Degrees of data；Then wave resistance is fitted by the linear fit instrument of excel softwares or the cross plot modules of geoview softwares The change type y=ax+b, y of anti-rotation porosity are porosity data, and x is Acoustic Impedance Data, and a, b are the parameter for needing to be fitted；2. in the case where studying the non-porous porosity log data in area：Using following formula (1), wave impedance is converted into porosity Data：Wherein, ACSolid skeletalRepresent the interval transit time of rock solid skeleton, ACFluidThe interval transit time of fluid between expression blowhole, IMP is Acoustic Impedance Data, and POR is porosity data；(5) transformational relation for the wave impedance turn hole porosity asked for using step (4), the hole number of degrees are converted to by Acoustic Impedance Data According to, obtain formation at target locations porosity data and be distributed, and drawing isoline figure；(6) 3-D seismics pure wave data, 3 kinds of extraction earthquake RMS amplitude, instantaneous phase, arc length seismic properties, to this are utilized Three kinds of seismic properties carry out cluster analysis, establish constraints based on borehole data, regression fit goes out a kind of new seismic properties Combination；(7) above-mentioned formation at target locations sand factor data, porosity distributed data and seismic properties combination distributed data are analyzed in intersection, Integrated forecasting Formation of Sandstone-type Uranium Deposits beneficial zone；Integrated forecasting Formation of Sandstone-type Uranium Deposits beneficial zone refers to the area for being more than X to numerical value in formation at target locations sand factor distribution map The region of domain, porosity value more than Y, region of the seismic properties combined value more than Z carry out intersection analysis and research, carry out into again accordingly The integrated forecasting of ore deposit beneficial zone.
- A kind of 2. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (1), lead to Seismic detector collection field 3D seismic data is crossed, the process handled field 3D seismic data is to carry out quiet school successively Just, denoising, amplitude compensation, deconvolution, dynamic school superposition, migration processing.
- A kind of 3. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (2), tool Body step is as follows：1. the foundation of initial model：The well data in collection research area first, sound wave curve therein and density curve are carried out Smoothing processing and standardization；2. establish inverting initial model using the STRATA modules of geoview softwares；3. wave impedance inversion calculates：The 3-D seismics pure wave data obtained to step (1) carry out Inversion Calculation, obtain three-dimensional wave resistance Anti- data volume；4. determine the threshold value of wave resistance anti-rotation lithology：The threshold value of the wave resistance anti-rotation lithology in each research area is not quite similar, threshold The determination of value is analyzed based on work area petrophysical parameter；5. lithology data calculates：The threshold value of the wave resistance anti-rotation lithology 4. obtained based on step (2), step (2) is 3. obtained Three-dimensional Wave Impedance Data Volume is converted to three-dimensional lithology data body, and the form of three-dimensional lithology data body is LITH (x, y, t), wherein x No. Inline of 3D seismic data is represented, y represents No. Xline of 3D seismic data, and t represents the time；The value of LITH (x, y, t) data volume is 0 or 1,0 expression mud stone, and 1 represents sandstone.
- A kind of 4. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 3, it is characterised in that：Step (2) 1. in, Use or 5 smoothing processings during smoothing processing at 3 points；3 points of density data or the processing of 5 moving averages are respectively as shown by the following formula：● 3 moving average formula of density：dden(i)=(dden(i-1)+dden(i)+dden(i+1))/3Wherein, diRepresent the density value of some sampled point, di-1For the density value of the previous sampled point of the sampled point, di+1For this The density value of the latter sampled point of sampled point；● 5 moving average formula of density：dden(i)=(dden(i-2)+dden(i-1)+dden(i)+dden(i+1)+dden(i+2))/5Wherein, diRepresent the density value of certain sampled point, di-2For the density value of the first two sampled point of the sampled point, di-1Adopted for this The density value of the previous sampled point of sampling point, di+1For the density value of the latter sampled point of the sampled point, di+2For the sampled point Latter two sampled point density value；3 points of sonic data or the processing of 5 moving averages are respectively as shown by the following formula：● 3 moving average formula of sound wave：dson(i)=(dson(i-1)+dson(i)+dson(i+1))/3Wherein, diRepresent the sound wave value of some sampled point, di-1For the sound wave value of the previous sampled point of the sampled point, di+1For this The sound wave value of the latter sampled point of sampled point；● 5 moving average formula of sound wave：dson(i)=(dson(i-2)+dson(i-1)+dson(i)+dson(i+1)+dson(i+2))/5Wherein, diRepresent the sound wave value of certain sampled point, di-2For the sound wave value of the first two sampled point of the sampled point, di-1Adopted for this The sound wave value of the previous sampled point of sampling point, di+1For the sound wave value of the latter sampled point of the sampled point, di+2For the sampled point Latter two sampled point sound wave value；Step (2) 1. in, handled using the logging nomalize modules of geoview softwares during standardization, will Sound wave and density data for the well of establishing initial model are normalized to same codomain scope；Step (2) 2. in, when establishing inverting initial model：When carrying out Inversion Calculation using the STRATA modules of geoview softwares, the setting of inverted parameters is：10-15Hz is high to be cut Frequently；Iterative times 10~20 times；Sample rate is 1ms~2ms；Maximum resistance variation scope is 25%~50%；Prewhitening rate is 1%；Computing block size is 1ms~2ms, and the computing block size is identical with sample rate；Scale factor is 1；Inverting type is multiple tracks inverting, Inline directions 10~20, Xline directions 10~20；Step (2) 4. in, the cross plot modules of petrophysical parameter analysis and utilization geoview softwares.
- A kind of 5. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (3), tool Body step is as follows：1. being based on 3-D seismics pure wave data input Landmark seismic interpretation softwares, it will explain that obtained three-dimensional formation data are led Enter in geoview softwares, the three-dimensional lithology data body of step (2) is imported into geoview softwares；2. determining destination layer scope, using the trace math modules of geoview softwares in the range of the bottom of destination layer top, followed Ring statistics calculates, and obtains stratum sand factor distributed data RATIO (x, y)；3. using, " trace math " modules need to write code, and specific code is as follows：Sand factor RATIO (x, y) distributed data of formation at target locations is can obtain accordingly；4. to step (3) 2. in sand factor RATIO (x, y) data, carry out isopleth into figure.
- A kind of 6. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (5), tool Body step is as follows：1. the conversion relational expression obtained using step (4), hole is calculated using the trace math modules of geoview softwares 3D data volume POR (x, y, t) is spent, x represents No. Inline of 3D seismic data, and y represents the Xline of 3D seismic data Number, t represents the time；2. determining destination layer scope, using the trace math modules of geoview softwares in the range of the bottom of destination layer top, followed Ring statistics calculates, and obtains formation at target locations average pore distributed data POR_AVA (x, y), and x represents 3D seismic data No. Inline, y represents No. Xline of 3D seismic data；The code write using trace math modules is as follows：3. porosity POR_AVA (x, y) distributed data of formation at target locations is can obtain accordingly；4. to step (5) 3. in obtained porosity POR_AVA (x, y) data, carry out isopleth into figure.
- A kind of 7. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：, will in step (6) Step (1) 3-D seismics pure wave data input into Landmark softwares, determines the position of target reservoir, each up and down in this position 3 kinds of extraction earthquake RMS amplitude, instantaneous phase, arc length seismic properties in 20ms thickness, then this three kinds of seismic properties are carried out Cluster analysis；The more attribute constraint situations of different zones are identified, restraint condition is in the practical application in Er'lian Basin sandstone-type uranium mining area： Earthquake RMS amplitude property value is more than 25, instantaneous phase property value and is more than 0, arc length property value more than 7, and regression fit goes out accordingly A kind of data of new seismic properties combination, and isogram is depicted as accordingly.
- A kind of 8. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (7), X, Y, the selection of Z values is according to the different and different of sandstone-type uranium mineralization with respect area；The method for obtaining X, Y, Z value is the institute by that will study in area There is industrial bore position to project respectively into formation at target locations sand factor distribution map, porosity distribution map, seismic properties constitutional diagram, read Take the sand factor value, porosity value, seismic properties combined value of all bore positions, then by these sand factor values, porosity value, Shake combinations of attributes value and carry out arithmetic average, obtain X, Y, Z value.
- A kind of 9. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：It is comprehensive in step (7) Closing prediction steps is：1. in the formation at target locations sand factor distribution map that step (3) obtains, region labeling of the codomain more than 0.8 is Favorable Areas A；2. in the formation at target locations average pore distribution map that step (5) is obtained, region labeling of the codomain more than 12% is favourable Area B；3. in the data isogram that the seismic properties that step (6) is obtained combine, region labeling of the codomain more than 0.45 is to have Sharp area C；4. overlap above-mentioned tri- Favorable Areas of A, B, C using graphics software, the overlapping intersection areas of three Favorable Areas of prediction for I classes into Ore deposit prospective area；It is II classes into ore deposit Favorable Areas to have the overlapping intersection area of two panels Favorable Areas in three Favorable Areas of prediction；Other situations Do not give a forecast.
- A kind of 10. sandstone-type uranium mineralization with respect Comprehensive Seismic Prediction method as claimed in claim 1, it is characterised in that：In step (1), field 3D seismic data, the process handled field 3D seismic data are gathered by seismic detector It is to carry out static correction, denoising, amplitude compensation, deconvolution, dynamic school superposition, migration processing successively；In step (2), comprise the following steps that：1. the foundation of initial model：The well data in collection research area first, sound wave curve therein and density curve are carried out Smoothing processing and standardization；Use or 5 smoothing processings during smoothing processing at 3 points；3 points of density data or the processing of 5 moving averages are respectively as shown by the following formula：● 3 moving average formula of density：dden(i)=(dden(i-1)+dden(i)+dden(i+1))/3Wherein, diRepresent the density value of some sampled point, di-1For the density value of the previous sampled point of the sampled point, di+1For this The density value of the latter sampled point of sampled point；● 5 moving average formula of density：dden(i)=(dden(i-2)+dden(i-1)+dden(i)+dden(i+1)+dden(i+2))/5Wherein, diRepresent the density value of certain sampled point, di-2For the density value of the first two sampled point of the sampled point, di-1Adopted for this The density value of the previous sampled point of sampling point, di+1For the density value of the latter sampled point of the sampled point, di+2For the sampled point Latter two sampled point density value；3 points of sonic data or the processing of 5 moving averages are respectively as shown by the following formula：● 3 moving average formula of sound wave：dson(i)=(dson(i-1)+dson(i)+dson(i+1))/3Wherein, diRepresent the sound wave value of some sampled point, di-1For the sound wave value of the previous sampled point of the sampled point, di+1For this The sound wave value of the latter sampled point of sampled point；● 5 moving average formula of sound wave：dson(i)=(dson(i-2)+dson(i-1)+dson(i)+dson(i+1)+dson(i+2))/5Wherein, diRepresent the sound wave value of certain sampled point, di-2For the sound wave value of the first two sampled point of the sampled point, di-1Adopted for this The sound wave value of the previous sampled point of sampling point, di+1For the sound wave value of the latter sampled point of the sampled point, di+2For the sampled point Latter two sampled point sound wave value；Handled during standardization using the logging nomalize modules of geoview softwares, will be used to establish initially The sound wave and density data of the well of model are normalized to same codomain scope；2. establish inverting initial model using the STRATA modules of geoview softwares；When carrying out Inversion Calculation using the STRATA modules of geoview softwares, the setting of inverted parameters is：10-15Hz is high to be cut Frequently；Iterative times 10~20 times；Sample rate is 1ms~2ms；Maximum resistance variation scope is 25%~50%；Prewhitening rate is 1%；Computing block size is 1ms~2ms, and the computing block size is identical with sample rate；Scale factor is 1；Inverting type is multiple tracks inverting, Inline directions 10~20, Xline directions 10~20；3. wave impedance inversion calculates：The 3-D seismics pure wave data obtained to step (1) carry out Inversion Calculation, obtain three-dimensional wave resistance Anti- data volume；4. determine the threshold value of wave resistance anti-rotation lithology：The threshold value of the wave resistance anti-rotation lithology in each research area is not quite similar, threshold The determination of value is analyzed based on work area petrophysical parameter；The cross plot modules of petrophysical parameter analysis and utilization geoview softwares；5. lithology data calculates：The threshold value of the wave resistance anti-rotation lithology 4. obtained based on step (2), step (2) is 3. obtained Three-dimensional Wave Impedance Data Volume is converted to three-dimensional lithology data body, and the form of three-dimensional lithology data body is LITH (x, y, t), wherein x No. Inline of 3D seismic data is represented, y represents No. Xline of 3D seismic data, and t represents the time；The value of LITH (x, y, t) data volume is 0 or 1,0 expression mud stone, and 1 represents sandstone；In step (3), comprise the following steps that：1. being based on 3-D seismics pure wave data input Landmark seismic interpretation softwares, it will explain that obtained three-dimensional formation data are led Enter in geoview softwares, the three-dimensional lithology data body of step (2) is imported into geoview softwares；2. determining destination layer scope, using the trace math modules of geoview softwares in the range of the bottom of destination layer top, followed Ring statistics calculates, and obtains stratum sand factor distributed data RATIO (x, y)；3. using, " trace math " modules need to write code, and specific code is as follows：Sand factor RATIO (x, y) distributed data of formation at target locations is can obtain accordingly；4. to step (3) 2. in sand factor RATIO (x, y) data, carry out isopleth into figure；In step (5), comprise the following steps that：1. the conversion relational expression obtained using step (4), hole is calculated using the trace math modules of geoview softwares 3D data volume POR (x, y, t) is spent, x represents No. Inline of 3D seismic data, and y represents the Xline of 3D seismic data Number, t represents the time；2. determining destination layer scope, using the trace math modules of geoview softwares in the range of the bottom of destination layer top, followed Ring statistics calculates, and obtains formation at target locations average pore distributed data POR_AVA (x, y), and x represents 3D seismic data No. Inline, y represents No. Xline of 3D seismic data；The code write using trace math modules is as follows：3. porosity POR_AVA (x, y) distributed data of formation at target locations is can obtain accordingly；5. to step (5) 3. in obtained porosity POR_AVA (x, y) data, carry out isopleth into figure；In step (6), step (1) 3-D seismics pure wave data input into Landmark softwares, is determined into the position of target reservoir Put, 3 kinds of earthquake RMS amplitude, instantaneous phase, arc length seismic properties are extracted in each 20ms thickness up and down in this position, then to this Three kinds of seismic properties carry out cluster analysis；The more attribute constraint situations of different zones are identified, restraint condition is in the practical application in Er'lian Basin sandstone-type uranium mining area： Earthquake RMS amplitude property value is more than 25, instantaneous phase property value and is more than 0, arc length property value more than 7, and regression fit goes out accordingly A kind of data of new seismic properties combination, and isogram is depicted as accordingly.In step (7), the selection of X, Y, Z value is according to the different and different of sandstone-type uranium mineralization with respect area；The method for obtaining X, Y, Z value is logical Cross by study area in all industrial bore positions project respectively to formation at target locations sand factor distribution map, porosity distribution map, Shake in combinations of attributes figure, read the sand factor value, porosity value, seismic properties combined value of all bore positions, then these are contained Sand coarse aggregate ratio value, porosity value, seismic properties combined value carry out arithmetic average, obtain X, Y, Z value；Integrated forecasting step is：1. in the formation at target locations sand factor distribution map that step (3) obtains, region labeling of the codomain more than 0.8 is Favorable Areas A；2. in the formation at target locations average pore distribution map that step (5) is obtained, region labeling of the codomain more than 12% is favourable Area B；3. in the seismic properties data splitting isogram that step (6) is obtained, region labeling of the codomain more than 0.45 is favourable Area C；4. overlap above-mentioned tri- Favorable Areas of A, B, C using graphics software, the overlapping intersection areas of three Favorable Areas of prediction for I classes into Ore deposit prospective area；It is II classes into ore deposit Favorable Areas to have the overlapping intersection area of two panels Favorable Areas in three Favorable Areas of prediction；Other situations Do not give a forecast.
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| CN108897041A (en) * | 2018-08-16 | 2018-11-27 | 中国石油天然气股份有限公司 | Prediction method and device for uranium ore enrichment area |
| CN109165436A (en) * | 2018-08-17 | 2019-01-08 | 中国地质科学院探矿工艺研究所 | Method for measuring source quantity of modern moraine type marine glacier |
| CN111257926A (en) * | 2018-12-03 | 2020-06-09 | 核工业二0八大队 | Method for predicting ancient valley uranium reservoir by using old seismic data |
| CN111257926B (en) * | 2018-12-03 | 2022-07-26 | 核工业二0八大队 | Method for predicting ancient valley uranium reservoir by using old seismic data |
| CN112764122B (en) * | 2019-10-21 | 2023-12-12 | 中国石油化工股份有限公司 | Method for confining uranium reservoir of ancient river channel sandstone |
| CN112764122A (en) * | 2019-10-21 | 2021-05-07 | 中国石油化工股份有限公司 | Delineation method of ancient river channel type sandstone uranium reservoir |
| CN111190240A (en) * | 2020-01-13 | 2020-05-22 | 吉林大学 | Extraction method of metallogenic structural elements of sandstone-type uranium deposits based on three-dimensional seismic interpretation |
| CN111190240B (en) * | 2020-01-13 | 2021-09-07 | 吉林大学 | Extraction method of metallogenic structural elements of sandstone-type uranium deposits based on three-dimensional seismic interpretation |
| CN111239815B (en) * | 2020-01-20 | 2021-07-13 | 吉林大学 | A method for extracting metallogenic and sedimentary elements of sandstone-type uranium reservoirs based on three-dimensional seismic attributes |
| CN111239815A (en) * | 2020-01-20 | 2020-06-05 | 吉林大学 | A method for extracting metallogenic and sedimentary elements of sandstone-type uranium reservoirs based on three-dimensional seismic attributes |
| CN111852467A (en) * | 2020-07-28 | 2020-10-30 | 核工业北京地质研究院 | A method and system for delineating the extension range of sandstone uranium ore body |
| CN111983721A (en) * | 2020-08-26 | 2020-11-24 | 核工业北京地质研究院 | Sandstone uranium ore mud-sand-mud geological structure identification method and system |
| CN113514886A (en) * | 2021-07-22 | 2021-10-19 | 核工业北京地质研究院 | A geological-seismic three-dimensional prediction method for favorable parts of sandstone-type uranium deposits |
| CN113514886B (en) * | 2021-07-22 | 2021-12-10 | 核工业北京地质研究院 | A geological-seismic three-dimensional prediction method for favorable parts of sandstone-type uranium deposits |
| CN113640873A (en) * | 2021-08-18 | 2021-11-12 | 核工业二0八大队 | Sandstone-type uranium ore prestack earthquake prediction method and device |
| CN113640873B (en) * | 2021-08-18 | 2024-04-12 | 核工业二0八大队 | Sandstone uranium ore pre-stack earthquake prediction method and device |
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